timma (version 1.2.1)

targetRank: Generate the list of ranked target combinations

Description

A function to provide a list of target combiantions ranked by their predicted synergy scores

Usage

targetRank(profile_select, predicted_matrix)

Arguments

profile_select

the drug-target interaction profile for the selected targets

predicted_matrix

the predicted efficacy matrix

Value

a matrix containing the list of target combinations

References

Tang J, Karhinen L, Xu T, Szwajda A, Yadav B, Wennerberg K, Aittokallio T. Target inhibition networks: predicting selective combinations of druggable targets to block cancer survival pathways. PLOS Computational Biology 2013; 9: e1003226.

Examples

## Not run: 
# data(tyner_interaction_binary)
# data(tyner_sensitivity)
# float<-sffsBinary(tyner_interaction_binary, tyner_sensitivity[, 1], max_k = 8)
# k_select<-float$k_sel
# x<-data.frame(tyner_interaction_binary)
# kinase_names <- dimnames(x)[[2]]
# select_kinase_names <- findSameSet(x, k_select, kinase_names)
# gc_timma <- graycode3(length(k_select))
# gc_names <- graycodeNames(length(k_select), select_kinase_names, gc_timma$gc_row, gc_timma$gc_col)
# nr <- gc_names$nr
# nc <- t(gc_names$nc)
# timma_row <- nrow(nr) + nrow(nc)
# timma_col <- ncol(nr) + ncol(nc)
# timma <- array("", dim = c(timma_row, timma_col))
# timma[(nrow(nc) + 1):timma_row, 1:ncol(nr)] <- nr
# timma[1:nrow(nc), (ncol(nr) + 1):timma_col] <- nc
# timma[(nrow(nc) + 1):timma_row, (ncol(nr) + 1):timma_col] <- float$timma$dummy
# profile_select<-data.frame(tyner_interaction_binary)[, k_select]
# target_combo_rank<-targetRank(profile_select, timma)
# ## End(Not run)